Update links to point to new repo

.github/PULL_REQUEST_TEMPLATE.md

@@ -15,7 +15,6 @@
 
 ### Relevant sources or documentation <!-- if any, otherwise delete -->
 
-
 ## Validation, testing, and comparison report(s)
 
 <!--

.github/workflows/python-app.yaml

@@ -46,8 +46,6 @@ jobs:
       - uses: julia-actions/setup-julia@5c9647d97b78a5debe5164e9eec09d653d29bd71 # v2
         with:
           version: ${{ env.JULIA_VERSION }}
-        env:
-          NODE_EXTRA_CA_CERTS: /usr/local/share/ca-certificates/nrel_ca_chain.crt
 
       - run: julia --project=. instantiate.jl
 
@@ -203,8 +201,6 @@ jobs:
         id: setup-julia
         with:
           version: ${{ env.JULIA_VERSION }}
-        env:
-          NODE_EXTRA_CA_CERTS: /usr/local/share/ca-certificates/nrel_ca_chain.crt
 
       - name: Restore Julia cache
         uses: actions/cache@5a3ec84eff668545956fd18022155c47e93e2684 # v4

CITATION.cff

@@ -60,7 +60,7 @@ authors:
     family-names: Turan
   - given-names: Max
     family-names: Vanatta
-url: 'https://www.nrel.gov/analysis/reeds/index.html'
+url: 'https://www.nlr.gov/analysis/reeds/index.html'
 abstract: >-
   The Regional Energy Deployment System (ReEDS) is
   NLR's flagship capacity planning model for the

CONTRIBUTING.md

@@ -2,8 +2,8 @@
 
 Community contributions to ReEDS are welcome and encouraged!
 
-For questions or general discussion, please open a [discussion](https://github.com/NatLabRockies/ReEDS-2.0/discussions). To report a bug, please open an [issue](https://github.com/NatLabRockies/ReEDS-2.0/issues).
+For questions or general discussion, please open a [discussion](https://github.com/ReEDS-Model/ReEDS/discussions). To report a bug, please open an [issue](https://github.com/ReEDS-Model/ReEDS/issues).
 
-To contribute code, fork the repository, make your changes, and submit a pull request. Please review our [Developer Guide](https://natlabrockies.github.io/ReEDS-2.0/developer_best_practices.html) before getting started.
+To contribute code, fork the repository, make your changes, and submit a pull request. Please review our [Developer Guide](https://reeds-model.github.io/ReEDS/developer_best_practices.html) before getting started.
 
-**Note:** if you're considering making a change that might lead to meaningful differences in model capability, workflow, or outputs, we recommend initiating a [discussion](https://github.com/NatLabRockies/ReEDS-2.0/discussions).
+**Note:** if you're considering making a change that might lead to meaningful differences in model capability, workflow, or outputs, we recommend initiating a [discussion](https://github.com/ReEDS-Model/ReEDS/discussions).

README.md

@@ -1,4 +1,4 @@
-## ReEDS 2.0
+## ReEDS
 **Regional Energy Deployment System (ReEDS) Model**
 
 

docs/source/developer_best_practices.md

@@ -566,7 +566,7 @@ The following are best practices that should be considered when reviewing pull r
   - Request changes as necessary and explain your reasoning
   - Remember that the PR submitter is ultimately responsible for the changes in the PR, not you, so give the PR review a good effort, but don't agonize over every detail. 
     - If reviewing a PR becomes too large of a chore, feel free to reach out to others on the team to be able to tackle the PR review jointly
-  - If necessary, make sure the [ReEDS documentation](https://pages.github.nrel.gov/ReEDS/ReEDS-2.0/index.html) was updated to reflect the code changes
+  - If necessary, make sure the [ReEDS documentation](https://reeds-model.github.io/ReEDS/index.html) was updated to reflect the code changes
     - Instructions for how to update the documentation can be found [here](#updating-the-reeds-documentation)
 
 

docs/source/faq.md

@@ -11,6 +11,7 @@
     - [How do I change the spatial resolution of a ReEDS case?](#how-do-i-change-the-spatial-resolution-of-a-reeds-case)
     - [How can I reduce solve time?](#how-can-i-reduce-solve-time)
     - [How often are updates made to ReEDS?](#how-often-are-updates-made-to-reeds)
+    - [Help, I'm getting lots of log messages about missing fonts](#help-im-getting-lots-of-log-messages-about-missing-fonts)
     - [What are the limitations, caveats, and known issues?](#what-are-the-limitations-caveats-and-known-issues)
       - [Capabilities that don't currently work](#capabilities-that-dont-currently-work)
       - [Assumptions](#assumptions)

docs/source/model_documentation.md

@@ -9,7 +9,7 @@ We are especially grateful to Walter Short who first envisioned and developed th
 Finally, we are grateful to all those who helped sponsor ReEDS model development and analysis, particularly supporters from the U.S. Department of Energy (DOE) but also others who have funded our work over the years.
 
 ```{admonition} Suggested Citation
-National Laboratory of the Rockies. ({{ cite_date_last_updated }}). *Model documentation — ReEDS 2.0*. https://natlabrockies.github.io/ReEDS-2.0/model_documentation.html
+National Laboratory of the Rockies. ({{ cite_date_last_updated }}). *Model documentation — ReEDS 2.0*. https://reeds-model.github.io/ReEDS/model_documentation.html
 
 ```
 
@@ -153,11 +153,11 @@ National Laboratory of the Rockies. ({{ cite_date_last_updated }}). *Model docum
 
 ## Introduction
 
-This documentation describes the structure and key data elements of the [Regional Energy Deployment System](https://www.nrel.gov/analysis/reeds/) (ReEDS) model, which is maintained and operated by the National Laboratory of the Rockies (NLR).
+This documentation describes the structure and key data elements of the [Regional Energy Deployment System](https://www.nlr.gov/analysis/reeds/) (ReEDS) model, which is maintained and operated by the National Laboratory of the Rockies (NLR).
 In this introduction, we provide a high-level overview of ReEDS objectives, capabilities, and applications.
 We also provide a short discussion of important caveats that apply to any ReEDS analysis.
 
-The ReEDS model code and input data can be accessed at <https://github.com/NatLabRockies/ReEDS-2.0>.
+The ReEDS model code and input data can be accessed at <https://github.com/ReEDS-Model/ReEDS>.
 
 
 ### Overview
@@ -199,7 +199,7 @@ ReEDS has been the primary analytical tool in numerous studies, including the Re
 ReEDS has also been used to examine the impacts of a range of existing and proposed energy policies {cite:p}`lantzImplicationsPTCExtension2014, maiImpactFederalTax2015, gagnonImpactRetailElectricity2017, steinbergEvaluatingImpactsInflation2023, denholmExaminingSupplySideOptions2022`.
 Transmission and grid integration studies often require scenarios of future power systems, and ReEDS has been used in such studies, e.g., the National Transmission Planning Study {cite}`doeNationalTransmissionPlanning2024`, the Atlantic Offshore Wind Transmission Study {cite}`brinkmanAtlanticOffshoreWind2024a`, and the North American Renewable Integration Study {cite}`brinkmanNorthAmericanRenewable2021a`.
 Many other studies, conducted by NLR and non-NLR researchers, use ReEDS to evaluate diverse topics relevant to the power sector.
-The [ReEDS website](https://www.nrel.gov/analysis/reeds/) includes a list of publications with NLR co-authorship that use ReEDS.
+The [ReEDS website](https://www.nlr.gov/analysis/reeds/) includes a list of publications with NLR co-authorship that use ReEDS.
 
 
 ### Summary of Caveats
@@ -1196,7 +1196,7 @@ As a result, its capital cost is uprated by the ratio of a 15-year evaluation wi
 Batteries are assumed to have a round-trip efficiency of 85% and a representative size of 60 MW.
 
 Existing PSH capacity is represented in the model according to the input plant database.
-New PSH potential is derived from a national PSH resource assessment described in {cite}`rosenliebClosedLoopPumpedStorage2022` and at <https://www.nrel.gov/gis/psh-supply-curves.html>.
+New PSH potential is derived from a national PSH resource assessment described in {cite}`rosenliebClosedLoopPumpedStorage2022` and at <https://www.nlr.gov/gis/psh-supply-curves.html>.
 Several PSH supply curves are available in ReEDS, including alternative storage durations (8, 10, or 12 hours) and alternative environmental site exclusions specifying whether new PSH reservoir construction can occur where there are ephemeral streams as defined by the National Hydrography Dataset, or whether to include sites that utilize existing reservoirs.
 The PSH resource assessment includes site-level capital costs calculated from a detailed bottom-up cost model that incorporates dam, reservoir, and other site characteristics {cite}`cohenComponentLevelBottomUpCost2023`.
 PSH fixed O&M costs and round-trip efficiency are taken from {cite}`mongird2020GridEnergy2020`, and PSH cost and resource assumptions are taken from the ATB {cite}`nrelAnnualTechnologyBaseline2024`.
@@ -1341,7 +1341,7 @@ At least 1% of the region's land area must overlap with the storage availability
 ReEDS requires any hydrogen storage be sized to hold at least 24 hours' worth of hydrogen to run the H<sub>2</sub>-CTs in a given region.
 
 ReEDS also allows the modeling of interzonal hydrogen transport.
-Transport requires the construction of hydrogen pipelines, and the model assumes cost estimates based on the H<sub>2</sub> [SERA model](https://www.nrel.gov/hydrogen/sera-model.html).
+Transport requires the construction of hydrogen pipelines, and the model assumes cost estimates based on the H<sub>2</sub> [SERA model](https://www.nlr.gov/hydrogen/sera-model.html).
 Modeling hydrogen transport in ReEDS is an experimental feature and, because this feature adds significant runtime, the model includes the option to model zonal balancing with transport disabled or a fixed \$/kg hydrogen transport cost.
 
 
@@ -3408,7 +3408,7 @@ To enable more detailed study of system operations, NLR has developed a translat
 expansion solution for any solve year in production cost models (PCMs).
 R2X supports translations to two PCMs: Sienna and PLEXOS.
 
-[Sienna](https://www.nrel.gov/analysis/sienna) is an open-source NLR modeling tool for scientific energy system analysis.
+[Sienna](https://www.nlr.gov/analysis/sienna) is an open-source NLR modeling tool for scientific energy system analysis.
 As part of its core capabilities, `Sienna\Ops` supports the simulation of system scheduling---including unit commitment and economic dispatch, automatic generation control, and nonlinear optimal power flow---along with sequential problem specifications to enable production cost modeling techniques.
 NLR has used Sienna in several analyses such as Puerto Rico 100 and the National Transmission Planning Study
 where it was used as the PCM tool for transmission planning and operational analysis for future scenarios {cite:p}`muralibagguPuertoRicoGrid2024, doeNationalTransmissionPlanning2024`.
@@ -3446,7 +3446,7 @@ such as a long-run marginal emission rate.[^ref64]
 [^ref64]: The long-run marginal emission rate is a metric designed to help estimate the emissions induced (or avoided) by a persistent change in electricity consumption.
 Unlike the short-run marginal emission rate, the long-run marginal emission rate reflects the structural changes to the grid that can be induced by a persistent change in electricity consumption.
 
-Datasets derived through Cambium can be viewed and downloaded at <https://cambium.nrel.gov/>.
+Datasets derived through Cambium can be viewed and downloaded at <https://www.nlr.gov/analysis/cambium/>.
 The documentation for Cambium contains descriptions of the metrics reported in the databases and the methods for calculating those metrics {cite}`gagnonCambium2022Scenario2023`.
 
 

docs/source/user_guide.md

@@ -112,7 +112,7 @@ The `GSw_LoadProfiles` switch corresponds to a file saved to `inputs/remote/dema
 
 | Switch Name    | Description of Profile | Origin | Weather year included |
 | ------------- | ------------- | ------------- | ------------- |
-| historic | Detrended historic demand from 2007-2013 and 2016-2023. This is multiplied by annual growth factors from AEO to forecast load growth. | Produced by the ReEDS team from a compilation of data sources. More detail can be found in the [hourlize readme](https://github.com/NatLabRockies/ReEDS-2.0/tree/main/hourlize). | 2007-2013 & 2016-2023 |
+| historic | Detrended historic demand from 2007-2013 and 2016-2023. This is multiplied by annual growth factors from AEO to forecast load growth. | Produced by the ReEDS team from a compilation of data sources. More detail can be found in the [hourlize readme](https://github.com/ReEDS-Model/ReEDS/tree/main/hourlize). | 2007-2013 & 2016-2023 |
 | EFS_Clean2035_LTS | Net-zero emissions, economy wide, by 2050 based on the White House's Long Term Strategy as shown here: <https://www.whitehouse.gov/wp-content/uploads/2021/10/US-Long-Term-Strategy.pdf> | Developed for the 100% Clean Electricity by 2035 study: <https://www.nrel.gov/docs/fy22osti/81644.pdf> |  2007-2013 |
 | EFS_Clean2035    | Accelerated Demand Electrification (ADE) profile. This profile was custom made for the 100% Clean Electricity by 2035 study. More information about how it was formed can be found in <https://www.nrel.gov/docs/fy22osti/81644.pdf> Appendix C. | Developed for the 100% Clean Electricity by 2035 study: <https://www.nrel.gov/docs/fy22osti/81644.pdf> |  2007-2013 |
 | EFS_Clean2035clip1pct | Same as Clean2035 but clips off the top 1% of load hours. | Developed for the 100% Clean Electricity by 2035 study: <https://www.nrel.gov/docs/fy22osti/81644.pdf> |  2007-2013 |
@@ -138,7 +138,7 @@ The `GSw_LoadProfiles` switch corresponds to a file saved to `inputs/remote/dema
 
 ### Different weather years
 
-For EER’s load profiles, “weather” includes everything considered by NLR's [ResStock](https://resstock.nrel.gov/) and [ComStock](https://comstock.nrel.gov/) building models (i.e., temperature, humidity, insolation, and wind speed). This information gets translated into variations in load through regressions and benchmarking with historical system load data for the weather year in question.
+For EER’s load profiles, “weather” includes everything considered by NLR's [ResStock](https://resstock.nlr.gov/) and [ComStock](https://comstock.nlr.gov/) building models (i.e., temperature, humidity, insolation, and wind speed). This information gets translated into variations in load through regressions and benchmarking with historical system load data for the weather year in question.
 
 ### Demand Response
 
@@ -162,7 +162,7 @@ The low cost scenario assumes further declines from 2030 to 2050.
 
 Fixed O&M values are assumed to be 5% of CAPEX (source: <https://iopscience.iop.org/article/10.1088/1748-9326/acacb5>)
 
-Electrolyzer performance (efficiency) as well as SMR cost and performance assumptions are derived from assumptions [H2A: Hydrogen Analysis Production Models](https://www.nrel.gov/hydrogen/h2a-production-models.html), with guidance from Paige Jadun.
+Electrolyzer performance (efficiency) as well as SMR cost and performance assumptions are derived from assumptions [H2A: Hydrogen Analysis Production Models](https://www.nlr.gov/hydrogen/h2a-production-models.html), with guidance from Paige Jadun.
 See original input assumptions in the [ReEDS_Input_Processing repo](https://github.com/ReEDS-Model/ReEDS_Input_Processing/blob/main/hydrogen/costs/H2ProductionCosts-20210414.xlsx).
 
 Note that SMR costs are currently in 2018$ and electrolyzer costs are in 2022$.

hourlize/README.md

@@ -51,7 +51,7 @@ Before running resource hourlize the reV runs should be copied from their origin
 Under the appropriate tech folder (UPV, ONSHORE, OFFSHORE, etc.) create a directory with a descrptive name for the supply curves (e.g., 2023_06_06_Update). Then copy the reV supply curves and profiles into a folder called `reV`. A good approach is to use rsync; below is an example copying original reV files from Eagle to Kestrel:
 
 ```bash
-rsync -aPu [username]@eagle.hpc.nrel.gov://shared-projects/rev/projects/seto/fy23/rev/standard_scenarios/aggregation/  /projects/shared-projects-reeds/reeds/Supply_Curve_Data/UPV/2023_06_06_Update/reV
+rsync -aPu [username]@kestrel.nlr.gov://shared-projects/rev/projects/seto/fy23/rev/standard_scenarios/aggregation/  /kfs2/shared-projects/reeds/Supply_Curve_Data/UPV/2023_06_06_Update/reV
 ```
 
 ### 2. Update the rev_paths files
@@ -80,7 +80,7 @@ By default hourlize will copy the required files in your ReEDS repository (`copy
 Note that hourlize copies to only one of the shared locations (either the HPC or nrelnas01, depending on where you are running it), so even with `copy_to_shared=True` you'll want to sync up the two shared folders. When starting from the HPC, be sure to open up permissions to the supply curve outputs you've just created (e.g., `chmod -R 777 UPV/2023_06_06_Update`). Then, from your local computer, use WinSCP or rsync to copy the files from Kestrel to nrelnas01:
 
 ```bash
-rsync -aPu [username]@kestrel.nrel.gov://projects/shared-projects-reeds/reeds/Supply_Curve_Data/UPV/2023_11_02_LandCover /Volumes/ReEDS/Supply_Curve_Data/UPV
+rsync -aPu [username]@kestrel.nlr.gov://projects/shared-projects-reeds/reeds/Supply_Curve_Data/UPV/2023_11_02_LandCover /Volumes/ReEDS/Supply_Curve_Data/UPV
 ```
 
 ## Running hourlize

inputs/emission_constraints/README.md

@@ -7,4 +7,4 @@ Upstream and process emission rates by technology and pollutant used in ReEDS ar
 Note that CH<sub>4</sub> upstream emission rate for natural gas is zero in `emitrate.csv` as we use CH<sub>4</sub> methane leakage defined using the `GSw_MethaneLeakageScen` switch to calculate it.
 
 ### Global Warming Potentials
-A range of values for global warmning potentals (GWP) of CH<sub>4</sub> and N<sub>2</sub>O are taken from the most recent IPCC assessment reports (AR4 to AR6). Summary of the ranges of GWPs for these pollutants can be found in Table 7.15, page 1017 of the IPCC AR6 report (https://www.ipcc.ch/report/ar6/wg1/downloads/report/IPCC_AR6_WGI_FullReport.pdf).
+A range of values for global warming potentials (GWP) of CH<sub>4</sub> and N<sub>2</sub>O are taken from the most recent IPCC assessment reports (AR4 to AR6). Summary of the ranges of GWPs for these pollutants can be found in Table 7.15, page 1017 of the IPCC AR6 report (https://www.ipcc.ch/report/ar6/wg1/downloads/report/IPCC_AR6_WGI_FullReport.pdf).

postprocessing/tableau/readme.md

@@ -14,10 +14,10 @@ This folder contains files that facilitate the postprocessing and publication of
 ### Step 1: Set up Tableau
 1. [Tableau](https://www.tableau.com/) is a commercial software that requires a license. Licenses are available through NLR overhead funds for no additional cost to projects. Request a license through the [Tableau catalog item](https://nrel.servicenowservices.com/sp?id=sc_cat_item_guide&sys_id=9c54d9cc874b7910496140070cbb35d7) in the IT Service portal. Under 'Product/Version', select 'Tableau Creator'. This includes Tableau Desktop and will allow you to edit Tableau workbooks, as opposed to purely viewing them. 
 2. Install [Tableau Desktop](https://www.tableau.com/products/desktop/download) on your local machine. IT will complete this with you with your license ticket, as submitted in Step 1.   
-3. Activate your license. IT will most likely complete this with you with your license ticket, as submitted in Step 1. If they do not, Tableau Desktop installations activate by authenticating to [Tableau Server](https://tableau.nrel.gov/). All licensed Tableau users have been added to the Server. The Server will activate Desktop installations for users assigned a Tableau Creator license. Note: Computers must be connected to NLR's enterprise network (onsite or by VPN) to authenticate to Tableau Server. To activate an existing installation of Tableau:
+3. Activate your license. IT will most likely complete this with you with your license ticket, as submitted in Step 1. If they do not, Tableau Desktop installations activate by authenticating to [Tableau Server](https://tableau.nlr.gov/). All licensed Tableau users have been added to the Server. The Server will activate Desktop installations for users assigned a Tableau Creator license. Note: Computers must be connected to NLR's enterprise network (onsite or by VPN) to authenticate to Tableau Server. To activate an existing installation of Tableau:
     - Open Tableau and go to Help > Manage Product Keys.  
     - Click the Activate button and select Activate by signing into a server.  
-    - In the Server field, enter https://tableau.nrel.gov
+    - In the Server field, enter https://tableau.nlr.gov
     - Click Connect
 
 ** If you are no longer using your Tableau license please let the ITS Asset Management team know so that the license seat can be used by someone else.